GORDON: Benchmarking Optane DC Persistent Memory Modules on FPGAs

2021 ◽  
Author(s):  
Jialiang Zhang ◽  
Nicholas Beckwith ◽  
Jing Jane Li
Keyword(s):  
Persistent Memory ◽  
Memory Modules

Octopus + : An RDMA-Enabled Distributed Persistent Memory File System

2021 ◽  
Vol 17 (3) ◽  
pp. 1-25
Author(s):  
Bohong Zhu ◽  
Youmin Chen ◽  
Qing Wang ◽  
Youyou Lu ◽  
Jiwu Shu
Keyword(s):  
High Speed ◽  
High Performance ◽  
File System ◽  
Direct Memory Access ◽  
File Systems ◽  
Distributed File Systems ◽  
Persistent Memory ◽  
Memory Modules ◽  
Non Volatile Memory ◽  
Volatile Memory

Non-volatile memory and remote direct memory access (RDMA) provide extremely high performance in storage and network hardware. However, existing distributed file systems strictly isolate file system and network layers, and the heavy layered software designs leave high-speed hardware under-exploited. In this article, we propose an RDMA-enabled distributed persistent memory file system, Octopus + , to redesign file system internal mechanisms by closely coupling non-volatile memory and RDMA features. For data operations, Octopus + directly accesses a shared persistent memory pool to reduce memory copying overhead, and actively fetches and pushes data all in clients to rebalance the load between the server and network. For metadata operations, Octopus + introduces self-identified remote procedure calls for immediate notification between file systems and networking, and an efficient distributed transaction mechanism for consistency. Octopus + is enabled with replication feature to provide better availability. Evaluations on Intel Optane DC Persistent Memory Modules show that Octopus + achieves nearly the raw bandwidth for large I/Os and orders of magnitude better performance than existing distributed file systems.

Persistent memory hash indexes

2021 ◽  
Vol 14 (5) ◽  
pp. 785-798
Author(s):  
Daokun Hu ◽  
Zhiwen Chen ◽  
Jianbing Wu ◽  
Jianhua Sun ◽  
Hao Chen
Keyword(s):  
Future Development ◽  
High Performance ◽  
Performance Metrics ◽  
Comprehensive Evaluation ◽  
State Of The Art ◽  
Hash Tables ◽  
Trade Offs ◽  
Depth Analysis ◽  
Persistent Memory ◽  
Memory Modules

Persistent memory (PM) is increasingly being leveraged to build hash-based indexing structures featuring cheap persistence, high performance, and instant recovery, especially with the recent release of Intel Optane DC Persistent Memory Modules. However, most of them are evaluated on DRAM-based emulators with unreal assumptions, or focus on the evaluation of specific metrics with important properties sidestepped. Thus, it is essential to understand how well the proposed hash indexes perform on real PM and how they differentiate from each other if a wider range of performance metrics are considered. To this end, this paper provides a comprehensive evaluation of persistent hash tables. In particular, we focus on the evaluation of six state-of-the-art hash tables including Level hashing, CCEH, Dash, PCLHT, Clevel, and SOFT, with real PM hardware. Our evaluation was conducted using a unified benchmarking framework and representative workloads. Besides characterizing common performance properties, we also explore how hardware configurations (such as PM bandwidth, CPU instructions, and NUMA) affect the performance of PM-based hash tables. With our in-depth analysis, we identify design trade-offs and good paradigms in prior arts, and suggest desirable optimizations and directions for the future development of PM-based hash tables.

scholarly journals Building blocks for persistent memory

2020 ◽  
Vol 29 (6) ◽  
pp. 1223-1241
Author(s):  
Alexander van Renen ◽  
Lukas Vogel ◽  
Viktor Leis ◽  
Thomas Neumann ◽  
Alfons Kemper
Keyword(s):  
Performance Evaluation ◽  
Building Blocks ◽  
Database Systems ◽  
Performance Bottlenecks ◽  
Persistent Memory ◽  
Comprehensive Performance ◽  
Memory Modules ◽  
Real Hardware ◽  
Writing Block ◽  
Level Building

AbstractI/O latency and throughput are two of the major performance bottlenecks for disk-based database systems. Persistent memory (PMem) technologies, like Intel’s Optane DC persistent memory modules, promise to bridge the gap between NAND-based flash (SSD) and DRAM, and thus eliminate the I/O bottleneck. In this paper, we provide the first comprehensive performance evaluation of PMem on real hardware in terms of bandwidth and latency. Based on the results, we develop guidelines for efficient PMem usage and four optimized low-level building blocks for PMem applications: log writing, block flushing, in-place updates, and coroutines for write latency hiding.

scholarly journals An Empirical Evaluation of NVM-Aware File Systems on Intel Optane DC Persistent Memory Modules

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1977
Author(s):  
Guangyu Zhu ◽  
Jaehyun Han ◽  
Sangjin Lee ◽  
Yongseok Son
Keyword(s):  
Data Management ◽  
Empirical Evaluation ◽  
File Systems ◽  
Data Management System ◽  
Nand Flash ◽  
Storage Devices ◽  
Persistent Memory ◽  
Memory Modules ◽  
And Performance ◽  
And Storage

The emergence of non-volatile memories (NVM) brings new opportunities and challenges to data management system design. As an important part of the data management systems, several new file systems are developed to take advantage of the characteristics of NVM. However, these NVM-aware file systems are usually designed and evaluated based on simulations or emulations. In order to explore the performance and characteristics of these file systems on real hardware, in this article, we provide an empirical evaluation of NVM-aware file systems on the first commercially available byte-addressable NVM (i.e., the Intel Optane DC Persistent Memory Module (DCPMM)). First, to compare the performance difference between traditional file systems and NVM-aware file systems, we evaluate the performance of Ext4, XFS, F2FS, Ext4-DAX, XFS-DAX, and NOVA file systems on DCPMMs. To compare DCPMMs with other secondary storage devices, we also conduct the same evaluations on Optane SSDs and NAND-flash SSDs. Second, we observe how remote NUMA node access and device mapper striping affect the performance of DCPMMs. Finally, we evaluate the performance of the database (i.e., MySQL) on DCPMMs with Ext4 and Ext4-DAX file systems. We summarize several observations from the evaluation results and performance analysis. We anticipate that these observations will provide implications for various memory and storage systems.

Scaling Dynamic Hash Tables on Real Persistent Memory

2021 ◽  
Vol 50 (1) ◽  
pp. 87-94
Author(s):  
Baotong Lu ◽  
Xiangpeng Hao ◽  
Tianzheng Wang ◽  
Eric Lo
Keyword(s):  
Hash Table ◽  
High Load ◽  
Low Latency ◽  
Load Factor ◽  
Hash Tables ◽  
Persistent Memory ◽  
Memory Modules

Byte-addressable persistent memory (PM) brings hash tables the potential of low latency, cheap persistence and instant recovery. The recent advent of Intel Optane DC Persistent Memory Modules (DCPMM) further accelerates this trend. Many new hash table designs have been proposed, but most of them were based on emulation and perform sub-optimally on real PM. They were also piecewise and partial solutions that side-stepped many important properties, in particular good scalability, high load factor and instant recovery.

How do memory modules differentially contribute to familiarity and recollection?

2019 ◽  
Vol 42 ◽  
Author(s):  
Olya Hakobyan ◽  
Sen Cheng
Keyword(s):  
Recognition Memory ◽  
Experimental Evidence ◽  
Subjective Experience ◽  
Target Article ◽  
Memory Modules ◽  
Familiarity And Recollection ◽  
Memory Contents

Abstract We fully support dissociating the subjective experience from the memory contents in recognition memory, as Bastin et al. posit in the target article. However, having two generic memory modules with qualitatively different functions is not mandatory and is in fact inconsistent with experimental evidence. We propose that quantitative differences in the properties of the memory modules can account for the apparent dissociation of recollection and familiarity along anatomical lines.

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